Industrial Anomaly Detection with Skip Autoencoder and Deep Feature Extractor

Over recent years, with the advances in image recognition technology for deep learning, researchers have devoted continued efforts toward importing anomaly detection technology into the production line of automatic optical detection. Although unsupervised learning helps overcome the high costs assoc...

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Detalles Bibliográficos
Autores principales: Tang, Ta-Wei, Hsu, Hakiem, Huang, Wei-Ren, Li, Kuan-Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737726/
https://www.ncbi.nlm.nih.gov/pubmed/36502029
http://dx.doi.org/10.3390/s22239327

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737726/
https://www.ncbi.nlm.nih.gov/pubmed/36502029
http://dx.doi.org/10.3390/s22239327

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